Robust approach to dynamic statistical process control

Statistical Process Control (SPC) technique are well established across a wide range of industries. In particular, the plotting of key steady state variables with their statistical limit against time (Shewart charting) is a common approach for monitoring the normality of production. This paper aims with extending Shewart charting techniques to the quality monitoring of variables driven by uncertain dynamic processes, which has particular application in the process industries where it is desirable to monitor process variables on-line as well as final product. The robust approach to dynamic SPC is based on previous work on guaranteed cost filtering for linear systems and is intended to provide a basis for both a wide application of SPC monitoring and also motivate unstructured fault detection.

Intermittency transport modeling of separated flow transition

An intermittency transport model is proposed for modeling separated-flow transition. The model is based on earlier work on prediction of attached flow bypass transition and is applied for the first time to model transition in a separation bubble at various degrees of free-stream turbulence. The model has been developed so that it takes into account the entrainment of the surrounding fluid. Experimental investigations suggest that it is this phenomena which ultimately determines the extent of the separation bubble. Transition onset is determined via a boundary layer correlation based on momentum thickness at the point of separation. The intermittent flow characteristic of the transition process is modeled via an intermittency transport equation. This accounts for both normal and streamwise variation of intermittency and hence models the entrainment of surrounding flow in a more accurate manner than alternative prescribed intermittency models. The model has been validated against the well established T3L semicircular leading edge flat plate test case for three different degrees of free-stream turbulence characteristic of turbomachinery blade applications.

Optical design of liquid crystal lenses: Off-axis modelling

We report on our work on producing liquid crystal switchable modal lenses and their use in a compound lens system in order to produce variable focus/zoom lenses. We describe work on producing a high power lens, and present theoretical work on off-axis phase modulation in a liquid crystal lens which is important in order to be able to carry out a complete optical design of a liquid crystal lens.

Low-order modelling of ducted flames with temporally varying equivalence ratio in realistic geometries

The interaction between unsteady heat release and acoustic pressure oscillations in gas turbines results in self-excited combustion oscillations which can potentially be strong enough to cause significant structural damage to the combustor. Correctly predicting the interaction of these processes, and anticipating the onset of these oscillations can be difficult. In recent years much research effort has focused on the response of premixed flames to velocity and equivalence ratio perturbations. In this paper, we develop a flame model based on the socalled G-Equation, which captures the kinematic evolution of the flame surfaces, under the assumptions of axisymmetry, and ignoring vorticity and compressibility. This builds on previous work by Dowling [1], Schuller et al. [2], Cho & Lieuwen [3], among many others, and extends the model to a realistic geometry, with two intersecting flame surfaces within a non-uniform velocity field. The inputs to the model are the free-stream velocity perturbations, and the associated equivalence ratio perturbations. The model also proposes a time-delay calculation wherein the time delay for the fuel convection varies both spatially and temporally. The flame response from this model was compared with experiments conducted by Balachandran [4, 5], and found to show promising agreement with experimental forced case. To address the primary industrial interest of predicting self-excited limit cycles, the model has then been linked with an acoustic network model to simulate the closed-loop interaction between the combustion and acoustic processes. This has been done both linearly and nonlinearly. The nonlinear analysis is achieved by applying a describing function analysis in the frequency domain to predict the limit cycle, and also through a time domain simulation. In the latter case, the acoustic field is assumed to remain linear, with the nonlinearity in the response of the combustion to flow and equivalence ratio perturbations. A transfer function from unsteady heat release to unsteady pressure is obtained from a linear acoustic network model, and the corresponding Green function is used to provide the input to the flame model as it evolves in the time domain. The predicted unstable frequency and limit cycle are in good agreement with experiment, demonstrating the potential of this approach to predict instabilities, and as a test bench for developing control strategies. Copyright © 2011 by ASME.

A Physical Interpretation of Stagnation Pressure and Enthalpy Changes in Unsteady Flow

This paper provides a physical interpretation of the mechanism of stagnation enthalpy and stagnation pressure changes in turbomachines due to unsteady flow, the agency for all work transfer between a turbomachine and an inviscid fluid. Examples are first given to illustrate the direct link between the time variation of static pressure seen by a given fluid particle and the rate of change of stagnation enthalpy for that particle. These include absolute stagnation temperature rises in turbine rotor tip leakage flow, wake transport through downstream blade rows, and effects of wake phasing on compressor work input. Fluid dynamic situations are then constructed to explain the effect of unsteadiness, including a physical interpretation of how stagnation pressure variations are created by temporal variations in static pressure; in this it is shown that the unsteady static pressure plays the role of a time-dependent body force potential. It is further shown that when the unsteadiness is due to a spatial nonuniformity translating at constant speed, as in a turbomachine, the unsteady pressure variation can be viewed as a local power input per unit mass from this body force to the fluid particle instantaneously at that point. © 2012 American Society of Mechanical Engineers.

Robust network reconstruction in polynomial time

This paper presents an efficient algorithm for robust network reconstruction of Linear Time-Invariant (LTI) systems in the presence of noise, estimation errors and unmodelled nonlinearities. The method here builds on previous work [1] on robust reconstruction to provide a practical implementation with polynomial computational complexity. Following the same experimental protocol, the algorithm obtains a set of structurally-related candidate solutions spanning every level of sparsity. We prove the existence of a magnitude bound on the noise, which if satisfied, guarantees that one of these structures is the correct solution. A problem-specific model-selection procedure then selects a single solution from this set and provides a measure of confidence in that solution. Extensive simulations quantify the expected performance for different levels of noise and show that significantly more noise can be tolerated in comparison to the original method. © 2012 IEEE.

Turbulence length scale measurements in a motored internal combustion engine

A novel technique, using a 'flying' Hot Wire Anemometer is described; it is shown how the turbulent structure in a motored engine, using a high molecular weight gas as the working fluid, may be investigated with relative simplicity and very little engine modification. Initial results are presented for integral and micro length scales, which are within the range expected based on previous work. Copyright © 1987 Society of Automotive Engineers, Inc.

Using sub-word-level information for confidence estimation with conditional random field models

The task of word-level confidence estimation (CE) for automatic speech recognition (ASR) systems stands to benefit from the combination of suitably defined input features from multiple information sources. However, the information sources of interest may not necessarily operate at the same level of granularity as the underlying ASR system. The research described here builds on previous work on confidence estimation for ASR systems using features extracted from word-level recognition lattices, by incorporating information at the sub-word level. Furthermore, the use of Conditional Random Fields (CRFs) with hidden states is investigated as a technique to combine information for word-level CE. Performance improvements are shown using the sub-word-level information in linear-chain CRFs with appropriately engineered feature functions, as well as when applying the hidden-state CRF model at the word level.

Stable multivariate rational interpolation for parameter-dependent aerospace models

A multivariate, robust, rational interpolation method for propagating uncertainties in several dimensions is presented. The algorithm for selecting numerator and denominator polynomial orders is based on recent work that uses a singular value decomposition approach. In this paper we extend this algorithm to higher dimensions and demonstrate its efficacy in terms of convergence and accuracy, both as a method for response suface generation and interpolation. To obtain stable approximants for continuous functions, we use an L2 error norm indicator to rank optimal numerator and denominator solutions. For discontinous functions, a second criterion setting an upper limit on the approximant value is employed. Analytical examples demonstrate that, for the same stencil, rational methods can yield more rapid convergence compared to pseudospectral or collocation approaches for certain problems. © 2012 AIAA.

Award Winner in the Young Investigator Category, 2014 Society for Biomaterials Annual Meeting and Exposition, Denver, Colorado, April 16-19, 2014: Periodically perforated core-shell collagen biomaterials balance cell infiltration, bioactivity, and mechanical properties.

Orthopedic tissue engineering requires biomaterials with robust mechanics as well as adequate porosity and permeability to support cell motility, proliferation, and new extracellular matrix (ECM) synthesis. While collagen-glycosaminoglycan (CG) scaffolds have been developed for a range of tissue engineering applications, they exhibit poor mechanical properties. Building on previous work in our lab that described composite CG biomaterials containing a porous scaffold core and nonporous CG membrane shell inspired by mechanically efficient core-shell composites in nature, this study explores an approach to improve cellular infiltration and metabolic health within these core-shell composites. We use indentation analyses to demonstrate that CG membranes, while less permeable than porous CG scaffolds, show similar permeability to dense materials such as small intestine submucosa (SIS). We also describe a simple method to fabricate CG membranes with organized arrays of microscale perforations. We demonstrate that perforated membranes support improved tenocyte migration into CG scaffolds, and that migration is enhanced by platelet-derived growth factor BB-mediated chemotaxis. CG core-shell composites fabricated with perforated membranes display scaffold-membrane integration with significantly improved tensile properties compared to scaffolds without membrane shells. Finally, we show that perforated membrane-scaffold composites support sustained tenocyte metabolic activity as well as improved cell infiltration and reduced expression of hypoxia-inducible factor 1α compared to composites with nonperforated membranes. These results will guide the design of improved biomaterials for tendon repair that are mechanically competent while also supporting infiltration of exogenous cells and other extrinsic mediators of wound healing.